On effective and efficient graph edge labeling

Journal article


Goonetilleke, Oshini, Koutra, Danai, Liao, Kewen and Sellis, Timos. (2019). On effective and efficient graph edge labeling. Distributed and Parallel Databases. 37(1), pp. 5-38. https://doi.org/10.1007/s10619-018-7234-4
AuthorsGoonetilleke, Oshini, Koutra, Danai, Liao, Kewen and Sellis, Timos
Abstract

Graphs, such as social, road and information networks, are ubiquitous as they naturally model entities and their relationships. Many query processing tasks on graphs are concerned about efficiently accessing nodes and edges stored in some order on disk or main memory. A natural following question we focus on here is: given a directed graph, how should we label/order its edges to achieve better disk locality and support various neighborhood queries efficiently? We answer this question by introducing two edge-labeling schemes, GRDRANDOM and FLIPINOUT, that label edges with natural number ordering based on the premise that edges should be assigned integer identifiers exploiting their consecutiveness to a maximum degree. We conduct extensive experimental analysis on real-world graphs, and compare our proposed schemes with various baseline labeling methods. We demonstrate that our methods are efficient and result in significantly improved query I/O performance. Finally, we propose an effective streaming graph partitioning method, FLIPCUT, which leverages the FLIPINOUT edge labeling.

Keywordsedge labeling; consecutiveness; query processing
Year2019
JournalDistributed and Parallel Databases
Journal citation37 (1), pp. 5-38
PublisherSpringer New York LLC
ISSN0926-8782
Digital Object Identifier (DOI)https://doi.org/10.1007/s10619-018-7234-4
Scopus EID2-s2.0-85051627165
Research or scholarlyResearch
Page range5-38
Publisher's version
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All rights reserved
File Access Level
Controlled
Output statusPublished
Publication dates
Online09 Aug 2019
Publication process dates
Deposited21 Dec 2021
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